Systems and methods for polarization control using blind source separation

ABSTRACT

Analog signal processing systems and methods manage polarization in coherent optical receivers to eliminate the need for ultra-fast, power-hungry ADCs and DSPs and that require digitization of the full-bandwidth signal path and result in bulky and expensive circuit designs. Various embodiments an analog polarization correction circuit that implements the equivalent of two matrix operations by combining variable and unity gain amplifiers to align polarizations of input signals to generate a polarization-corrected output signal that is aligned with the polarization frame of reference of a receiver. Various embodiments use BSS to perform polarization control, including electro-optical polarization control, in a feedback loop and operate without the need for a pilot tone or a startup sequence when deducing the polarization state.

CROSS-REFERENCE TO RELATED APPLICATIONS

This patent application is a continuation of and claims priority toco-pending and commonly-owned U.S. patent application Ser. No.16/379,316, entitled “Systems and Methods for Polarization Control UsingBlind Source Separation,” naming as inventors Charles John Razzell andfiled Apr. 9, 2019, which claims priority benefit under 35 U.S.C. §119(e) to commonly-owned U.S. Provisional Patent Application No.62/682,599, entitled “Systems and Methods for Polarization Control UsingBlind Source Separation,” naming as inventor Charles John Razzell, andfiled Jun. 8, 2018, which patent documents are incorporated by referenceherein in their entirety and for all purposes.

TECHNICAL FIELD

The present disclosure relates generally to electrical signalprocessing. More particularly, the present disclosure related to systemsand methods for controlling and recovering polarization and carrierphase in electro-optical communication systems.

BACKGROUND

Coherent optical communication links at rates of 100 Gbps/λ and higherhave been commercially deployed in recent years. These systems heavilyrely on power-hungry (e.g., >10 W) digital signal processing (DSP)devices even for cutting-edge CMOS process technologies (e.g., 16 nmlinewidths in commercial products). The ability to support unamplifiedlinks of up to 80 km at such high rates justifies the cost of powerfulDSPs in light of a reduction of other capital expenses and operatingcosts. On the other hand, the ever-increasing demand for high bandwidthcommunications within data centers is pushing direct-detection,intensity modulation four-level pulse amplitude modulation (PAM4)schemes to their limits.

For example, IEEE P802.3cd is expected to standardize as one of its PHYoptions, 100GBASE-DR, 100 Gb/s serial transmission over one wavelengthusing PAM4 over of single-mode fiber >500 m. Results from contributorsto the IEEE P802.3cd task group, shown in FIG. 1 (IEEE SMF Task GroupContribution by Marco Mazzini (Cisco), August 2014), indicate that 56Gbaud/112 Gbps PAM4 requires a feed-forward equalizer to open the eye.Although some approaches have demonstrated feasibility, numerouscontributions indicate that meeting link budget margins for this type ofPHY option remains challenging.

One type of distortion that a polarized optical input beam that passesthrough an optical fiber plant experiences relates to undesirablechanges to the state of polarization (SOP) of the signal that occurduring transmission. In order to avoid having to manipulate polarizationstates in the DSP domain, which would normally be the expectation for aDSP-based coherent receiver, some designers have proposed to implementpolarization control by using optical modulators. To facilitate this, apilot or marker tone is added at the transmitter to label and track oneof the phases of the two polarizations (e.g., the x-polarization,in-phase signal branch) as a reference, such that a control loopalgorithm running in a low-power CPU can monitor and adjust thepolarization states to correct for polarization rotations in two orthree degrees of freedom.

The pilot tone (e.g., 50 kHz) that has been superimposed onto the XItributary at the transmitter is used to recover the state ofpolarization at the receiver that low-pass filters the XQ, YI, and YQsignals and synchronously detects these signals in the four branches.Thus, the receiver monitors the amplitudes and signs of these signals,while assuming that carrier phase lock has already been achieved. Lowspeed signal processing can then be used to adjust the polarizationangles to reduce the unwanted pilot tone amplitudes, such that thereceiver can compensate for polarization rotation in the fiber. However,this approach suffers from drawbacks related to a bootstrap problem,namely that (1) marker tone detection is possible only after carrierphase recovery, and (2) the carrier recovery depends on the polarizationstates having first been corrected, e.g., to ensure that a QPSKconstellation is available for detection.

One proposed solution to alleviate these drawbacks involves a transmitstartup protocol, wherein the same data is simultaneously transmitted ineach of the two polarization branches. This requirement allows thecarrier recovery loop to “see” QPSK modulation regardless ofpolarization state, such that carrier phase lock can be achieved. In asecond step, the polarization recovery loop is enabled, with theexpectation that the 50 kHz marker tone will now be found at theexpected frequency. However, such a solution is less than ideal because(1) special startup sequences may not be feasible in a system contextdue to compatibility reasons (e.g., lack of suitable protocols that canfacilitate a special startup sequence), and (2) if DQPSK is used, nophase-locked system is present, such that the ability to synchronouslydetect the pilot tone, which hinges on a phase-locked system, is lost.As a result, each time lock is lost for any reason, the link has to bebroken and restarted causing undesirable disruptions to the operation.

Accordingly, what is needed are systems and methods that operatepilot-less and startup sequence-free when deducing the polarizationstate.

BRIEF DESCRIPTION OF THE DRAWINGS

References will be made to embodiments of the invention, examples ofwhich may be illustrated in the accompanying figures. These figures areintended to be illustrative, not limiting. Although the invention isgenerally described in the context of these embodiments, it should beunderstood that it is not intended to limit the scope of the inventionto these particular embodiments.

FIG. 1 illustrates the limitations of PAM4 modulation schemes proposedin the prior art that require a feed-forward equalizer.

FIG. 2 illustrates an exemplary block diagram of a receiver architecturethat senses polarization via digital subsampling, according variousembodiments of the present disclosure.

FIG. 3 is a flowchart for applying polarization control based on blindsource estimation, according various embodiments of the presentdisclosure.

FIG. 4 illustrates an exemplary block diagram of a receiver architecturethat uses electronic feedback control to perform carrier phasecorrection, according various embodiments of the present disclosure.

FIG. 5 is a flowchart for applying polarization and carrier phasecontrol based on blind source estimation, according various embodimentsof the present disclosure.

FIG. 6 is a flowchart for coherent combining of two receiver brancheswith initially unknown relative phase, according various embodiments ofthe present disclosure.

FIG. 7 is a flowchart for coherent combining of two receiver brancheswith initially unknown relative phase to implement polarizationdiversity, according various embodiments of the present disclosure.

FIG. 8 is an illustrative block diagram of an exemplary optical receivercircuit that implements reception of a transmit polarization diversityscheme organized using a Space-Time Block Coding (STBC) scheme,according various embodiments of the present disclosure.

FIG. 9 is a flowchart of an illustrative process for channel estimationfor STBC-encoded diversity transmitters, in accordance with variousembodiments of the present disclosure.

FIG. 10 depicts a 16-QAM transmitter modulation vector diagram (withadded noise).

FIG. 11 depicts simulated DP-16-QAM power spectra.

FIG. 12 depicts simulation results that show a scatter plot for a 16-QAMreceiver that uses no polarization correction.

FIG. 13-FIG. 15 depict high-level simulation results illustratingscatter plots for a 16-QAM receiver that utilizes EFICA, FicaCMPLX, andJADE, respectively, according to various embodiments of the presentdisclosure.

DETAILED DESCRIPTION OF THE EMBODIMENTS

In the following description, for purposes of explanation, specificdetails are set forth in order to provide an understanding of theinvention. It will be apparent, however, to one skilled in the art thatthe invention can be practiced without these details. Furthermore, oneskilled in the art will recognize that embodiments of the presentinvention, described below, may be implemented in a variety of ways,such as a process, an apparatus, a system, a device, or a method on atangible computer-readable medium.

Components, or modules, shown in diagrams are illustrative of exemplaryembodiments of the invention and are meant to avoid obscuring theinvention. It shall also be understood that throughout this discussionthat components may be described as separate functional units, which maycomprise sub-units, but those skilled in the art will recognize thatvarious components, or portions thereof, may be divided into separatecomponents or may be integrated together, including integrated within asingle system or component. It should be noted that functions oroperations discussed herein may be implemented as components. Componentsmay be implemented in software, hardware, or a combination thereof.

Furthermore, connections between components or systems within thefigures are not intended to be limited to direct connections. Rather,data between these components may be modified, re-formatted, orotherwise changed by intermediary components. Also, additional or fewerconnections may be used. It shall also be noted that the terms“coupled,” “connected,” or “communicatively coupled” shall be understoodto include direct connections, indirect connections through one or moreintermediary devices, and wireless connections.

Reference in the specification to “one embodiment,” “preferredembodiment,” “an embodiment,” or “embodiments” means that a particularfeature, structure, characteristic, or function described in connectionwith the embodiment is included in at least one embodiment of theinvention and may be in more than one embodiment. Also, the appearancesof the above-noted phrases in various places in the specification arenot necessarily all referring to the same embodiment or embodiments.

The use of certain terms in various places in the specification is forillustration and should not be construed as limiting. A service,function, or resource is not limited to a single service, function, orresource; usage of these terms may refer to a grouping of relatedservices, functions, or resources, which may be distributed oraggregated. Furthermore, the use of memory, database, information base,data store, tables, hardware, and the like may be used herein to referto system component or components into which information may be enteredor otherwise recorded.

It is noted that: (1) certain steps may optionally be performed; (2)steps may not be limited to the specific order set forth herein; (3)certain steps may be performed in different orders; and (4) certainsteps may be done concurrently. For example, while examples are given inthe context of blind source separation (BSS) methods applied to opticalreceivers, one skilled in the art will recognize that the teachings ofthe present disclosure are not limited to the BSS applications describedherein and may equally be applied individually, jointly, orsimultaneously, in any combination and in other contexts, e.g., inapplications that may or may not involve carrier phase recovery.

Various embodiments advantageously use low-rate (e.g., sample rates inthe order of 10 MHz) digital samples of the XI, XQ, YI, and YQ andestimate the unknown, complex Jones 2×2 matrix, which describes thepolarization transformation in the fiber plant, from the samples of XI,XQ, YI and YQ without prior information. In embodiments, the complexJones matrix is estimated by treating it as a mixing matrix and applyingto the resulting signal vectors a suitable BSS method, such as forexample, (1) Joint Approximate Diagonalization of Eigen-matrices (JADE);(2) Fast Fixed-Point Algorithm for Independent Component Analysis ofComplex Valued Signals (cFAST-ICA); and (3) Efficient Variant ofAlgorithm FastICA for Independent Component Analysis (EFICA). In short,once the problem is framed as a BSS problem, it may then be solved byselecting and using an appropriate method for solving the resulting BSSproblem by using a BSS method that operates on complex matrices toseparate out the polarizations at the receiver without having to resortto pilot tones, startup sequences, or any other suboptimal techniques.

Since these methods rely only on the statistical properties of datasets, e.g., to optimize separation into independent components,advantageously, estimating the Jones matrix using BSS is not bound toNyquist sampling according to the Baud rate of the communications signalto obtain satisfactory results. In fact, in embodiments, massiveundersampling (e.g., by several orders of magnitude), which is limitedonly by the update rate for the SOP changes in the fiber plant, may beemployed. In addition, undersampling advantageously reducescomputational complexity and power consumption for computing, e.g.,updates to a receiver's polarization control state variables (e.g., ϕand θ).

In embodiments, a sample rate much lower than the signal bandwidthNyquist rate may be used, while sample-and-hold and ADC circuits (e.g.,in the front-end) are configured to operate without applying excessivelow pass filtering that, otherwise, may cause the statistics to shifttowards Gaussian statistics, for example, due to the Central LimitTheorem. Therefore, in embodiments, a high bandwidth sample-and-holdcircuit is paired with a modest sample rate ADC to acquire data, thus,avoiding the use of expensive ultra-high, multi-bit speed ADCs in thesignal path.

FIG. 2 illustrates an exemplary block diagram of a receiver architecturethat senses polarization via digital subsampling, according variousembodiments of the present disclosure. In FIG. 2, receiver 200 isdepicted as a dual polarization M-QAM receiver; however, this is notintended as a limitation on the scope of the disclosure, of course.Receiver circuit 200 is an optical receiver that may comprise opticalfront-end 202, and analog polarization correction circuit 204,differential modulator circuit 208.

In embodiments, optical front-end 202, comprises photo-diodes 203, PBS250, 90°-hybrid 256, and local oscillator 260. Optical front-end 202 maybe any optical front-end known in the art. In embodiments, analogpolarization correction circuit 204 may comprise amplifiers 205-207 andprocesses the output of photo-diodes 203 to isolate two polarizationstreams prior to differential detection by differential modulatorcircuit 208. Differential modulator circuit 208 may comprise low-passfilters 210, ADCs 280, memory buffers (e.g., RAM), sample-and-holdcircuits 282, timing recovery and bit slicing modules 214, 216, andpolarization controller 212 (e.g., a microcontroller) that may outputangles 242 and 244 and performs a non-linear operation that involvessquaring of amplitudes.

In embodiments, input signal 240 is comprised of independent bit streamsin the X-polarization and the Y-polarization that are separated fromeach other in receiver 200 in order to access the independent bitstreams. In embodiments, this is accomplished by undoing arbitrary,unknown rotations in at least two degrees of freedom that input signal240 may undergo in fiber channel and that may otherwise affect eachother.

In detail, optical front-end 202 receives, e.g., via PBS 250, inputsignal 240, e.g., from an optical channel. PBS 250 separates inputsignal 240 into two components, X and Y, that are orthogonalpolarizations in two branches, i.e., an X-polarization branch 252 and aY-branch 254. In embodiments, X-polarization branch 252 is input to90°-hybrid 256, e.g., a six-port hybrid, and Y-polarization 254 branchis input to 90°-hybrid 256.

In embodiments, hybrid 256, 258 may comprise a connection for localoscillator 260, such as a laser. It is noted that in an ideal homodynereceiver, local oscillator 260 operates on the same wavelength as theto-be-decoded signal. In practice, drift and tolerances may result inless than ideal conditions, such that wavelengths are not exactly thesame.

In embodiments, hybrid 256 creates different phases based on thesummation of its input signals. In embodiments, in the top branch thatcomprises hybrid 256, the local oscillator signal is summed with theX-polarization signal 252, and hybrid 256 outputs four phases, e.g., 0°,180°, 90°, and 270°. Conversely, Y-polarization is processed in thebottom branch by hybrid 258 to output, e.g., four signals having fourphases and in the same order as hybrid 254.

Photo-diodes 203 may be differential photo-diodes that, in embodiments,process light, which has positive amplitude, i.e., photo-diodes 203themselves do not generate negative signals. In embodiments, the outputsof adjacent photo-diodes 203 are electrical current signals that are180° out-of-phase and that represent the difference of, e.g., the 0°output of hybrid 256 and the 180° output, i.e., a bipolar photo currentthat may assume both positive or negative values. The difference in thephoto currents is a signal that represents the in-phase component Xi, ofX-polarization signal 252. Similarly, photo-diodes 203 on the 90° outputand the 270° output generate a bipolar photo current that representsquadrature component, Xq, of the X-polarization signal 252, and so on.Overall, hybrids 256, 258 may each output two electrical signals inbalanced pairs, e.g., Xi and Xq that refer to in-phase polarization andquadrature polarization, respectively. It is understood that these fourelectrical signals may be amplified, filtered, and further processedthroughout the rest of receiver 200.

In embodiments, in-phase signal, Xi, and quadrature signal, Xq, areinput to analog polarization correction circuit 204 that rotates thephases of the signals in the X-polarization branch relative to the phaseof the y-polarization signal. In embodiments, an emphasis on therelative value of the phase difference allows to rotate theX-polarization values while not rotating the Y-polarization values. Asillustrated in FIG. 2, this may be accomplished by employing the fouramplifiers (e.g., 202) in the X-polarization branch to rotate the phaseangles ϕ of the input signals of the amplifiers, while not rotating thephase angles of the input signals of amplifiers (e.g., 204) in theY-polarization branch that may have unity gain.

The rotated signals may then be processed, e.g., by the set of eightamplifiers 206 that, in embodiments, act as θ-rotators that rotate thecombination of the in-phase and quadrature signals such as to align themwith the X- and Y-coordinates of receiver 200 in a manner that theybecome separated. As a result, the output of the θ-rotators ispolarization-corrected, thus, providing for a clean separation of thepolarization signals. One skilled in the art will appreciate that, inembodiments, a negative sign may be moved into the function of anamplifier itself, for example by commutating differential signal pairs.

In embodiments, the separated polarization signals are provided todifferential modulator circuit 208, e.g., to find the phase rotations.The phase angles θ of the output of analog polarization correctioncircuit 204 represent phase differences that may be processed usingconventional bit-slicing and timing recovery to obtain the actual bitstream.

In embodiments, polarization controller may be used to output two phaseangles ϕ and θ that, in turn, may control the specific weights of thegains of the two sets of amplifiers to efficiently undo the polarizationrotation in the fiber channel, such that the output of those summationblocks in analog polarization correction circuit 204 are corrected forpolarization and are the same signal as was originally transmittedindependently in two channels. In other words, the blocks of amplifiersmay be controlled in a feedback loop by phase angles ϕ and θ tosuccessfully accomplish that task and resolve the two polarizations,i.e., the X- and Y-polarization branches of the receiver, separately toobtain orthogonal signals in the two branches prior to processing themusing differential detection, etc., in a subsequent block of mixers.

In embodiments, polarization controller 212 may be implemented as amodest complexity hardware component, such as an ARM core, by takingadvantage of the sub-sampling of data received in four memory buffers(not shown) to reduce signal processing computation rates to manageablelevels. In embodiments, polarization controller 212, ADCs 280, andsample-and-hold circuits 282 in FIG. 2 are configured to facilitate datacollection by memory buffers that accumulate sufficient statistics thatallows controller 212 to run a BSS method, such as JADE, FAST-ICA, orEFICA, e.g., to manipulate a demixing matrix such as to obtain angles242, 244 that then may be derived and used for estimating polarizationstates in a continuous feedback loop. In embodiments, signals in thefour branches of receiver 200 may be sampled after they have beencorrected for polarization, but before a non-linear processing step thatmay be used for differential demodulation that demixes the polarization.

In embodiments, ADCs 280 may be implemented as low complexity ADCs thatuse a relatively low sample rate, e.g., in the order of a few MHz, whichmay be sufficient to keep up with the rate of change/rotation ofpolarization in the fiber plant based on the Nyquist rate for thehighest frequency for the polarization/phase rotation, present noimpediment to BSS. In embodiments, the bandwidths of sample-and-holdcircuits 282 are chosen to be compatible with the sampled signals.

FIG. 3 is a flowchart for applying polarization control based on blindsource estimation, according various embodiments of the presentdisclosure. In embodiments, the method may be implemented, e.g., by areceiver having an architecture similar to that shown in FIG. 2. Process300 in FIG. 3 may begin at step 302, when polarization control statevariables are initialized, e.g., such that θ₀=0 and ϕ₀=0.

At step 304, using a set of sample-and-hold and ADC circuits in areceiver, obtain a number of samples from the XI, XQ, YI, and YQbranches of the receiver and accumulate the samples into a set of memorybuffers. One skilled in the art will appreciate that samples may beacquired concurrently.

At step 306, BSS may be performed, e.g., by applying Complex ICA to thesamples in the memory buffers accumulated at step 304.

At step 308, the demixing matrix (e.g., 2×2) may be adjusted to becomeunitary. In embodiments, this may be accomplished using any of themethods described below.

At step 310, the resulting demixing matrix may be factorized to obtainincremental angles, e.g., Δϕ and Δθ.

At step 312, the incremental angles may be added to the previous statevariables θ_(k+1)=θ_(k)+Δθ and ϕ_(k+1)=ϕ_(k)+Δϕ to obtain updatedpolarization state variables {θ_(k+1), ϕ_(k+1)}.

At step 314, the updated polarization state variables {θ_(k+1), ϕ_(k+1)}may be written to the receiver hardware; process 300 may resume withstep 304.

In embodiments, in addition to polarization control applications, thesystems and methods described herein may be extended to carrier phaseestimation or recovery applications, e.g., for coherent modulationschemes, as described in the following paragraphs.

1. Simultaneous, Joint Recovery of Polarization and Carrier Phase

In embodiments, the complex Jones matrix may be factorized intoindividual rotations according to four degrees of freedom. Thus, theinverse of the Jones matrix, i.e., demixing matrix J⁻¹, may be expressedas:

$\begin{matrix}{J^{- 1} = {{{{e^{- \frac{j\; \psi}{2}}\begin{bmatrix}e^{- \frac{j\; \varphi_{0}}{2}} & 0 \\0 & e^{\frac{j\; \varphi_{0}}{2}}\end{bmatrix}}\begin{bmatrix}{\cos \; \theta} & {{- \sin}\; \theta} \\{\sin \; \theta} & {\cos \; \theta}\end{bmatrix}}\begin{bmatrix}e^{- \frac{j\; \varphi_{1}}{2}} & 0 \\0 & e^{\frac{j\; \varphi_{1}}{2}}\end{bmatrix}}.}} & \left( {{Eq}.\mspace{14mu} 1} \right)\end{matrix}$

In embodiments, instead of resolving the values of ϕ₀ and ψ, whichrepresent the absolute carrier phases in the X- and Y-polarizationbranches, by using means such as Differential Demodulation or an analogCostas loop, the complete demixing matrix J⁻¹ may be obtained by usingBSS to also perform carrier phase recovery, i.e., in addition recoveringin-phase and quadrature components for the X- and Y-polarization modes.

FIG. 4 illustrates an exemplary block diagram of a receiver architecturethat uses electronic feedback control to perform carrier phasecorrection, according various embodiments of the present disclosure. Asdepicted in FIG. 4, receiver 400 is a dual polarization M-QAM receiver.However, this is not intended as a limitation. For purposes of brevity,a description of similar components previously described with respect toFIG. 2 and their function is not repeated here.

Receiver 400 comprises carrier phase correction 410 that injects carrierphase information into receiver 400. FIG. 4 is an exemplaryimplementation that illustrates where absolute carrier phase control maybe applied in the analog domain according to updates that have beencomputed using BSS computed in a suitable microcontroller. Forconvenience, ϕ₀ and ψ have been reformulated as phase angles δ and ϵ inthe diagram.

In theory, preventing the mixing of I and Q components is expected towork well for square or rectangular signal constellations, such as4-QAM, 16-QAM, but less well for circular constellations, such as 8-PSK,or higher, because in order for the carrier phase estimates to beadequately estimated, the degree of independence of the informationresolved into the receiver's in-phase and quadrature channels should bea strong function of the rotation of the signal constellation.

FIG. 5 is a flowchart for applying polarization and carrier phasecontrol based on blind source estimation, according various embodimentsof the present disclosure. In embodiments, the method may beimplemented, e.g., by a receiver having an architecture similar to thatshown in FIG. 4. Process 500 may begin, at step 502, when polarizationcontrol state variables and carrier phase state variables areinitialized, e.g., such that θ₀=0, ϕ₀=0 and δ₀=0, ϵ₀=0.

At step 504, using a set of sample-and-hold and ADC circuits in areceiver, obtain a number of samples from the XI, XQ, YI, and YQbranches of the receiver and accumulate the samples into a set of memorybuffers. One skilled in the art will appreciate that samples should beacquired concurrently.

At step 506, BSS may be performed, e.g., by applying Complex ICA to thesamples in the memory buffers accumulated at step 504.

At step 508, the demixing matrix (e.g., 2×2) may be adjusted to becomeunitary. In embodiments, this may be accomplished using any of themethods described below.

At step 510, the resulting demixing matrix may be factorized to obtainincremental angles, e.g., Δϕ, Δθ, Δδ and Δϵ.

At step 512, the incremental angles may be added to the previous statevariables θ_(k+1)=θ_(k)+Δθ, ϕ_(k+1)=ϕ_(k)+Δϕ, δ_(k+1)=δ_(k)+Δδ andϵ_(k+1)=ϵ_(k)+Δϵ to obtain updated polarization state variables{θ_(k+1), ϕ_(k+1)} and carrier phase state variables {δ_(k+1), ϵ_(k+1)}that may be written to the receiver hardware; and process 500 may resumewith step 504.

2. Use of Complex or Real Versions of ICA

In embodiments, instead of treating the mixing matrix as beingequivalent to a 2×2 complex Jones matrix, J, and using complex versionsthe ICA algorithms to estimate J, the two complex data streams output bythe (four) branches of the receiver may be treated as four real datastreams that produce signals that may unmixed using, e.g., a 4×4 realmatrix instead of a 2×2 complex matrix. Therefore, in embodiments, eachoutput may be viewed as the product of four unknown mixing coefficientsand respective four input signals.

$\begin{matrix}{\begin{bmatrix}E_{rxi} \\E_{rxq} \\E_{ryi} \\E_{ryq}\end{bmatrix} = {{\begin{bmatrix}{\left\{ J_{11} \right\}} & {- \left\{ J_{11} \right\}} & {\left\{ J_{12} \right\}} & {- \left\{ J_{12} \right\}} \\{\left\{ J_{11} \right\}} & {\left\{ J_{11} \right\}} & {\left\{ J_{12} \right\}} & {\left\{ J_{12} \right\}} \\{\left\{ J_{21} \right\}} & {- \left\{ J_{21} \right\}} & {\left\{ J_{22} \right\}} & {- \left\{ J_{22} \right\}} \\{\left\{ J_{21} \right\}} & {\left\{ J_{21} \right\}} & {\left\{ J_{22} \right\}} & {\left\{ J_{22} \right\}}\end{bmatrix}\begin{bmatrix}E_{txi} \\E_{txq} \\E_{tyi} \\E_{tyq}\end{bmatrix}}.}} & \left( {{Eq}.\mspace{14mu} 2} \right)\end{matrix}$

By writing J as a real matrix in this manner, the real and imaginaryparts of each of the four elements of J are used twice. However, if areal ICA algorithm is used to estimate the 16-element mixing matrix,there would be 16 degrees of freedom in the estimate, and the pairs ofcoefficients that should be numerically equal to each other may be onlyapproximately equal, e.g., due to additional noise. Therefore, inembodiments, when interpreting a matrix, such as the above 4×4 matrix,as a Jones matrix that has less, here four, degrees of freedom, twoaveraging steps may be performed to obtain the benefits of averaging.The first step may yield, e.g., a complex 2×2 matrix based on the 16values in the 4×4 matrix; and the second step may yield a complexunitary matrix based on the complex, e.g., 2×2 matrix.

In embodiments, the first step may provide an estimate of J as given byexpression

$\begin{matrix}{\hat{J} = {{\frac{1}{2}\begin{bmatrix}{\left( {M_{11} + M_{22}} \right) +} & {\left( {M_{13} + M_{24}} \right) + {j\left( {M_{23} - M_{14}} \right)}} \\{j\left( {M_{21} - M_{12}} \right)} & \; \\{\left( {M_{31} + M_{42}} \right) +} & {\left( {M_{33} + M_{44}} \right) + {j\left( {M_{43} - M_{34}} \right)}} \\{j\left( {M_{41} - M_{32}} \right)} & \;\end{bmatrix}}.}} & \left( {{Eq}.\mspace{14mu} 3} \right)\end{matrix}$

However, this expression may be valid only if the 4×4 mixing matrix hasnot permuted the imaginary part of the Y-polarization with the imaginarypart of the X-polarization or the real part of the Y-polarization withthe imaginary part of the X-polarization.

In other words, rows 1 and 2 should belong to the same complex numberbefore undertaking this kind of averaging. In embodiments, at most, onepair of rows may need to be swapped to meet this criterion. The row that“belongs” with row 1 can be found by using a permuted, and selectivelynegated version of the first row as a predicted value for the second rowand finding the closest match amongst the candidate rows 2, 3 and 4.

In embodiments, the second step involves forcing this matrix to beunitary. If Ĵ is invertible, then the closest unitary matrix to Ĵ is

$\begin{matrix}{{= {\left( {\hat{J} \cdot {\hat{J}}^{\prime}} \right)^{- \frac{1}{2}}\hat{J}}},} & \left( {{Eq}.\mspace{14mu} 4} \right)\end{matrix}$

where the prime superscript indicates conjugate transpose and

$( \cdot )^{- \frac{1}{2}}$

indicates the inverse of the matrix square root.

In embodiments, the expression for

results in a unitary matrix that, advantageously, reduces the number ofdegrees of freedom down to, here, four, which aids in noise reduction.

It is noted that although the fiber plant polarization rotation can beexpressed as a unitary matrix, certain implementation impairments in theoptical front end may not be unitary. For example, finite extinctionratios in a polarization beam splitter or polarization dependent lossesmay lead to a non-unitary transfer matrix. Depending on the magnitude ofthese impairments, forcing the demixing matrix to be unitary may makethe estimation worse than if this step were omitted. Hence this step,should be applied in systems where the unitary approximation holdswithin an acceptable error tolerance.

FIG. 6 is a flowchart for coherent combining of two receiver brancheswith initially unknown relative phase, according various embodiments ofthe present disclosure. In embodiments, the method may be implemented,e.g., by a receiver having an architecture similar to that shown in FIG.4. Process 600 may begin, at step 602, when four row vectors thatrepresent XI, XQ, YI, and YQ receiver branch signals are verticallyconcatenated such as to form a 4×N matrix.

At step 604, a real-valued BSS is performed to obtain a 4×4 demixingmatrix.

At step 606, any row permutations that may have separated complexvariables into non-adjacent rows (e.g., using the correlationcoefficient as a comparison metric after permuting and inverting theappropriate columns) is undone.

At step 608, a first estimate of the 2×2 complex demixing matrix isobtained, e.g., by using the following averaging method:

$\begin{matrix}{\hat{J} = {{\frac{1}{2}\begin{bmatrix}{\left( {M_{11} + M_{22}} \right) +} & {\left( {M_{13} + M_{24}} \right) + {j\left( {M_{23} - M_{14}} \right)}} \\{j\left( {M_{21} - M_{12}} \right)} & \; \\{\left( {M_{31} + M_{42}} \right) +} & {\left( {M_{33} + M_{44}} \right) + {j\left( {M_{43} - M_{34}} \right)}} \\{j\left( {M_{41} - M_{32}} \right)} & \;\end{bmatrix}}.}} & \left( {{Eq}.\mspace{14mu} 5} \right)\end{matrix}$

At step 610, a method may be applied to force Ĵ to be unitary, e.g.,using

$\begin{matrix}{= {\left( {\hat{J} \cdot {\hat{J}}^{\prime}} \right)^{- \frac{1}{2}}{\hat{J}.}}} & {\left( {{Eq}.\mspace{14mu} 6} \right),}\end{matrix}$

which uniquely determines the closest unitary matrix to Ĵ, therebyimproving the quality of the estimate in cases where the impairments inthe fiber plant and receiver do not significantly deviate from unitaryones.

3. Application of Real FICA to Carrier Phase Estimation Recovery forPolarization Diversity Combining

As mentioned previously, in embodiments, different information may besent in two orthogonal polarization modes of a fiber, and BSS separationmay be used to determine a mixing matrix for the four branches of areceiver, e.g., by considering them as four real or two complex signalstreams.

In embodiments, when the same information is encoded on two orthogonalpolarizations, coherent combining of the orthogonal polarizationbranches of the receiver may be used to implement polarizationdiversity. In such instances, the only rotations that may need to berecovered to enable successful polarization diversity combining are thecarrier phases. Assuming that the I and Q channels of the receivercomprise independent information, in embodiments, ICA may be used oneach pair of I and Q channels to estimate rotations that render the realand imaginary components substantially or entirely independent. Inembodiments, such methods of carrier recovery may be preferable to otherdecision-directed methods for carrier recovery of 16-QAM or higher ordermodulations that generally work effectively only when the majority oftentative decisions are correct.

FIG. 7 is a flowchart for coherent combining of two receiver brancheswith initially unknown relative phase to implement polarizationdiversity, according various embodiments of the present disclosure. Inembodiments, polarization diversity may be implemented, e.g., by areceiver having an architecture similar to that shown in FIG. 4. Process700 may begin, at step 702, when real ICA is performed on a pair ofsignal buffers representing XI- and XQ-branches of a receiver.

At step 704, a resulting 2×2 demixing matrix may be made orthogonal,e.g., by adding or subtracting the adjugate, e.g. according to the signof the real part of its determinant.

At step 706, the resulting demixing (i.e., phase derotation) matrix maybe applied to the XI- and XQ-branch signal buffers, e.g., by matrixmultiplying the 2×2 demixing matrix with a 2×N matrix that comprises XI-and XQ-signal buffers as respective matrix rows.

At step 708, process 700 may return to step 702 using a different pairof signal buffers that represent YI- and YQ-branches of the receiver. Atthis point, the two X- and Y-branches may have been corrected forcarrier phase, subject to a 90-degree relative phase ambiguity.

At step 710, the argument of the complex dot product of thephase-corrected X-and Y-signals may be computed; and the resulting anglemay be quantized to the nearest multiple of 90 degrees, e.g., to resolvethe remaining 90-degree phase ambiguity.

At step 712, the 0, 90, 180, or 270-degree rotation computed in step 712may be applied to the Y-polarization signal buffer to bring it intophase alignment with the X-polarization signal buffer.

At step 714, the phase-corrected X-signal (computed at step 706) may besummed with phase-corrected Y-signal (computed at step 712).

At step 716, the weights found by the norms of the mixing matrixes forthe X- and Q-branches may be applied to adjust the gain of the tworeceiver branches so as to approximate Maximal Ratio Combining, therebyoptimizing the SNR of the combined signal.

4. Application of Complex FICA to Blind Channel Estimation for SpaceTime Block Code (STBC)-Encoded Diversity Transmitters

In embodiments, polarization diversity is obtained using an orthogonalblock code at the transmitter. This allows the receiver block to besimplified to one branch, thus, making the optical front-end much lessonerous to implement. The resulting polarization specificity in thereceiver may be compensated by the transmitter's ability tosimultaneously transmit in two orthogonal polarizations, while ensuringthat signals remain distinct due an orthogonal encoding scheme. FIG. 8is an illustrative block diagram of an exemplary optical receivercircuit that implements reception of a transmit polarization diversityscheme organized using a Space-Time Block Coding (STBC) scheme,according various embodiments of the present disclosure.

As depicted in FIG. 8, homodyne, digital receiver 800 is a dualpolarization DQPSK receiver that comprises a DSP-based STBC transmissionpolarization diversity M-QAM receiver 860. Receiver 800 comprises asingle polarization branch, e.g., the top half of FIG. 8, that, inembodiments, requires a channel estimate that is given by h₁ and h₂.

In embodiments, a common orthogonal frequency division multiplexing(OFDM) approach may be employed. For simplicity, for a single-carrierapproach, pairs of adjacent QAM symbols may be transmitted in a pair oforthogonal polarizations followed by a conjugated and negated conjugatecopy of the same pair of symbols transposed. An example of an encodedblock may be symbolically expressed as:

$\begin{matrix}{X\text{:}} & x_{1} & \; & {- x_{2}^{*}} \\{Y\text{:}} & x_{2} & \; & x_{1}^{*} \\\; & \; & \underset{time}{\rightarrow} & \;\end{matrix}\quad$

In embodiments, at the receiver, complex channel tap estimates may beused to express a relationship between the transmitter's X-polarizationframe of reference and the receiver's polarization frame of reference(h₁); and from the transmitter's Y-polarization frame of reference tothe receiver's polarization frame of reference (h₂). Coefficients h₁ andh₂ may be formed into a 2×2 matrix

$\begin{matrix}{{H = \begin{bmatrix}h_{1} & h_{2} \\{- h_{2}^{*}} & {- h_{1}^{*}}\end{bmatrix}},} & \left( {{Eq}.\mspace{14mu} 7} \right)\end{matrix}$

thus, the original symbols may be recovered using the expression

$\begin{matrix}{{\begin{bmatrix} \\x_{2}\end{bmatrix} = {\left( {H^{H}H} \right)^{- 1}{H^{H}\begin{bmatrix}y_{1} \\y_{2}^{*}\end{bmatrix}}}},} & \left( {{Eq}.\mspace{14mu} 8} \right)\end{matrix}$

where (H^(H)H)⁻¹H^(H) is known as the pseudo inverse of matrix H.

However, since matrix H is unknown, in embodiments, H is estimated byusing BSS techniques, e.g., by forming, in a buffer memory, a 2×Ncomplex matrix of mixed symbols as follows:

$\begin{matrix}{\begin{bmatrix}y_{1} & y_{3} & y_{5} & \; & y_{{2N} - 1} \\\; & \; & \; & \ldots & \; \\y_{2}^{*} & y_{4}^{*} & y_{6}^{*} & \; & y_{2N}^{*}\end{bmatrix}.} & \left( {{Eq}.\mspace{14mu} 9} \right)\end{matrix}$

In embodiments, an algorithm, e.g., an ICA algorithm may then beemployed that uses the 2×N matrix as input data to find a demixingmatrix D, e.g., a 2×2 matrix. In embodiments, the estimation quality ofD may be improved by forcing D to be unitary, e.g., by any suitablemethod previously described.

In embodiments, the demixing matrix D is assumed to be a reasonableapproximation of the pseudo inverse of matrix H (i.e.,D≅(H^(H)H)⁻¹H^(H)), such that D may be substituted for (H^(H)H)⁻¹H^(H)to estimate the separated symbols in their original state, e.g.,according to the expression

$\begin{matrix}{\begin{bmatrix}x_{1} & x_{3} & & \; & x_{{2N} - 1} \\\; & \; & \; & \ldots & \; \\x_{2} & x_{4} & x_{6} & \; & x_{2N}\end{bmatrix} = {{D\;\begin{bmatrix}y_{1} & y_{3} & y_{5} & \; & y_{{2N} - 1} \\\; & \; & \; & \ldots & \; \\y_{2}^{*} & y_{4}^{*} & y_{6}^{*} & \; & y_{2N}^{*}\end{bmatrix}}.}} & \left( {{Eq}.\mspace{14mu} 10} \right)\end{matrix}$

In embodiments, since the resulting symbols may be subject to arotational uncertainty of an integer multiple of 90 degrees (i.e., 90,180, 270), such uncertainty may be resolved using any method known inthe art, such as continuous pilot tones or a preamble, that may providean appropriate external reference, e.g., to zero phase.

FIG. 9 is a flowchart of an illustrative process for channel estimationfor STBC-encoded diversity transmitters, in accordance with variousembodiments of the present disclosure. In embodiments, process 900 aidsin obtaining estimates of original symbols may be implemented, e.g., bya receiver having an architecture similar to that shown in FIG. 8.Process 900 in FIG. 9 may begin, at step 902, when using a set ofsample-and-hold and ADC circuits in a receiver, obtain, e.g., at theNyquist rate (one sample per symbol) a number of samples from the XI andXQ branches of a receiver and accumulate the samples into a set ofmemory buffers. One skilled in the art will appreciate that samples maybe acquired concurrently.

At step 904, it may be determined that the XI and XQ buffers are filledwith valid symbols, if so, process 900 may resume with step 906, whenthe odd-numbered symbols may be arranged in the first row of a 2×Nmatrix of mixed symbols and the conjugated values of the even-numberedsymbols arranged in the second row.

At step 908, an ICA method that uses the 2×N matrix of mixed symbols asinput data may be employed to estimate a demixing matrix, D. Inembodiments, real or complex-valued ICA may be used according topreference, using any of the previously described methods.

At step 910, the estimated demixing matrix D may be applied to the 2×Nmixed symbols matrix, e.g., by using matrix multiplication to form

$\begin{matrix}{\begin{bmatrix}x_{1} & x_{3} & & \; & x_{{2N} - 1} \\\; & \; & \; & \ldots & \; \\x_{2} & x_{4} & x_{6} & \; & x_{2N}\end{bmatrix} = {{D\;\begin{bmatrix}y_{1} & y_{3} & y_{5} & \; & y_{{2N} - 1} \\\; & \; & \; & \ldots & \; \\y_{2}^{*} & y_{4}^{*} & y_{6}^{*} & \; & y_{2N}^{*}\end{bmatrix}}.}} & \left( {{Eq}.\mspace{14mu} 11} \right)\end{matrix}$

At step 912, {x₁, x₂, x₃ . . . x_(2N)} may be taken as the estimatedtransmitted symbols and perform symbol slicing, forward error correctionetc. according to the modulation type employed, at which point process900 may resume with step 904.

One skilled in the art will appreciate that the performance of thedisclosed embodiments for carrier recovery and/or polarizationcorrection may depend on the particular ICA method used.

5. Simulation of 16-QAM Polarization Correction and Carrier Recovery

FIG. 10-FIG. 15 depict simulation results for various embodiments of thepresent disclosure. Implementations using two independent 16-QAMmodulation streams that are sampled at 12 samples per symbol and utilizeBessel lowpass filtering to perform 5th-order Bessel pulse shaping havebeen simulated. Results indicate that a Baud rate of 50 Gbaud may yield400 Gbps/λ.

FIG. 10 depicts a 16-QAM transmitter modulation vector diagram (withadded noise).

FIG. 11 depicts simulated DP-16-QAM power spectra.

FIG. 12 depicts simulation results that show a scatter plot for a 16-QAMreceiver that uses no polarization correction.

FIG. 13 depicts simulation results illustrating a scatter plot for a16-QAM receiver that utilizes EFICA according to various embodiments ofthe present disclosure.

FIG. 14 depicts simulation results illustrating a scatter plot for a16-QAM receiver that utilizes FicaCMPLX according to various embodimentsof the present disclosure.

FIG. 15 depicts simulation results illustrating a scatter plot for a16-QAM receiver that utilizes JADE according to various embodiments ofthe present disclosure.

All three methods, EFICA, FicaCMPLX, and JADE proved capable ofresolving the polarization rotations. As the scatter plots in FIG. 13and FIG. 14 illustrate, EFICA and FicaCMPLX correctly resolved thecarrier phases, whereas JADE did not, as can be observed from thesimulation results in FIG. 15. A comparison FIG. 13 and FIG. 14illustrates that EFICA delivered superior results when compared toFicaCMPLX.

It is noted that the high-level simulation results presented herein areprovided by way of illustration and were performed under specificconditions using specific embodiments. Accordingly, neither thesesimulations nor their results shall be used to limit the scope of thedisclosure of the current patent document.

6. System Embodiments

Aspects of the present invention may be encoded upon one or morenon-transitory computer-readable media with instructions for one or moreprocessors or processing units to cause steps to be performed. It shallbe noted that the one or more non-transitory computer-readable mediashall include volatile and non-volatile memory. It shall be noted thatalternative implementations are possible, including a hardwareimplementation or a software/hardware implementation.Hardware-implemented functions may be realized using ASIC(s),programmable arrays, digital signal processing circuitry, or the like.Accordingly, the “means” terms in any claims are intended to cover bothsoftware and hardware implementations. Similarly, the term“computer-readable medium or media” as used herein includes softwareand/or hardware having a program of instructions embodied thereon, or acombination thereof. With these implementation alternatives in mind, itis to be understood that the figures and accompanying descriptionprovide the functional information one skilled in the art would requireto write program code (i.e., software) and/or to fabricate circuits(i.e., hardware) to perform the processing required.

It shall be noted that embodiments of the present invention may furtherrelate to computer products with a non-transitory, tangiblecomputer-readable medium that have computer code thereon for performingvarious computer-implemented operations. The media and computer code maybe those specially designed and constructed for the purposes of thepresent invention, or they may be of the kind known or available tothose having skill in the relevant arts. Examples of tangiblecomputer-readable media include, but are not limited to: magnetic mediasuch as hard disks, floppy disks, and magnetic tape; optical media suchas CD-ROMs and holographic devices; magneto-optical media; and hardwaredevices that are specially configured to store or to store and executeprogram code, such as application specific integrated circuits (ASICs),programmable logic devices (PLDs), flash memory devices, and ROM and RAMdevices. Examples of computer code include machine code, such asproduced by a compiler, and files containing higher level code that areexecuted by a computer using an interpreter. Embodiments of the presentinvention may be implemented in whole or in part as machine-executableinstructions that may be in program modules that are executed by aprocessing device. Examples of program modules include libraries,programs, routines, objects, components, and data structures. Indistributed computing environments, program modules may be physicallylocated in settings that are local, remote, or both.

One skilled in the art will recognize no computing system or programminglanguage is critical to the practice of the present invention. Oneskilled in the art will also recognize that a number of the elementsdescribed above may be physically and/or functionally separated intosub-modules or combined together.

It will be appreciated to those skilled in the art that the precedingexamples and embodiments are exemplary and not limiting to the scope ofthe present disclosure. It is intended that all permutations,enhancements, equivalents, combinations, and improvements thereto thatare apparent to those skilled in the art upon a reading of thespecification and a study of the drawings are included within the truespirit and scope of the present disclosure. It shall also be noted thatelements of any claims may be arranged differently including havingmultiple dependencies, configurations, and combinations.

What is claimed is:
 1. A method for analog polarization control usingblind source separation (BSS), the method comprising: sampling data fromXI, XQ, YI, and YQ branches of a receiver to obtain sampled data; usingthe sampled data in a controller-to perform a BSS; factorizing ademixing matrix to obtain incremental angles; adding the incrementalangles to a set of polarization control state variables to obtainupdated polarization control state variables; and using the updatedpolarization control state variables to perform polarization control. 2.The method according to claim 1, further comprising adjusting a demixingmatrix to become unitary.
 3. The method according to claim 1, whereinobtaining updated polarization state variables comprises obtainingupdated carrier phase state variables.
 4. The method according to claim1, further comprising: in response to receiving a first set of outputsignals having a first phase and a second set of output signals having asecond phase, rotating, by a first phase angle, the first phase of oneor more signals in the first set of output signals relative to thesecond phase of one or more signals in the second set of output signalsto generate a set of rotated signals; and rotating the set of rotatedsignals by a second phase angle to align the set of rotated signals witha polarization frame of reference.
 5. The method according to claim 4,wherein rotating the set of rotated signals reduces at least a componentof the second set of output signals from the first set of outputsignals.
 6. The method according to claim 4, wherein rotating the firstphase comprises adjusting a gain that is defined by a set oftrigonometric weights that correspond to the first and second phaseangles.
 7. The method according to claim 6, further comprising adjustinga polarity of the gain by adjusting relative transconductances ofparallel differential amplifiers that are coupled in oppositepolarities.
 8. The method according to claim 6, further comprisingadjusting gains of one or more amplifiers or attenuators in a pluralityof signal paths representing a complex number representation ofamplitude and phase of each polarization component.
 9. A method foranalog polarization control using blind source separation (BSS), themethod comprising: sampling data from XI, XQ, YI, and YQ branches of areceiver to obtain sampled data; and using the sampled data in acontroller that performs a BSS to adjust a demixing matrix to obtainphase angles that represent phase differences; using the phase angles toobtain polarization state estimates; using the polarization stateestimates to perform a polarization correction to obtainpolarization-corrected signals; and demodulating thepolarization-corrected signals.
 10. The method according to claim 9,further comprising using a feedback loop to estimate the polarizationstate estimates.
 11. The method according to claim 9, furthercomprising: factorizing the adjusted demixing matrix to obtainincremental angles; adding the incremental angles to the set ofpolarization control state variables to obtain updated polarizationcontrol state variables; and using the updated polarization controlstate variables to perform at last one of polarization control orcarrier phase recovery.
 12. The method according to claim 9, wherein thesampling is performed at a sampling rate lower than a signal bandwidthNyquist rate to reduce power consumption.
 13. The method according toclaim 12, wherein the sampling rate is greater than an update rate forstate-of-polarization changes.
 14. The method according to claim 13,wherein reducing power consumption comprises conserving computationalresources for computing updates to the receiver's control statevariables.
 15. The method according to claim 9, further comprising priorto performing the BSS, selecting a BSS method from one of jointapproximate diagonalization of eigen-matrices, fast fixed-pointalgorithm for independent component analysis of complex valued signals(cFAST-ICA), or efficient variant of algorithm fastICA for independentcomponent analysis.
 16. A method for coherent combining of two receiverbranches with initially unknown relative phase, the method comprising:vertically concatenating row vectors representing XI, XQ, YI, and YQreceiver branch signals to form a matrix; performing a blind sourceseparation (BSS) to obtain a demixing matrix; using correlation metricsto determine whether adjacent rows of the demixing matrix are associatedwith a same complex number; in response to determining that the adjacentrows are not associated with the same complex number, reordering one ormore rows of the demixing matrix to obtain adjacent rows that areassociated with the same complex number; obtaining an estimate of acomplex demixing matrix; and using the estimate to determinepolarization states in a polarization recovery loop.
 17. The methodaccording to claim 16, wherein performing the BSS comprises: samplingdata from XI, XQ, YI, and YQ branches of a receiver coupled to a fiberto obtain sampled data; and estimating a polarization transformation inthe fiber by using at least some of the sampled data, wherein estimatingthe polarization transformation comprises: using the sampled data in acontroller that performs the BSS to adjust the demixing matrix; andfactorizing the demixing matrix into a series of elementary rotationmatrices, wherein each elementary rotation matrix represents one degreeof freedom of the polarization rotation transformation.
 18. The methodaccording to claim 16, further comprising adjusting a demixing matrix tobecome unitary.
 19. The method according to claim 16, further comprisingadjusting gains of one or more amplifiers or attenuators in a pluralityof signal paths representing a complex number representation ofamplitude and phase of each polarization component.